Month: September 2017

A Bit of Background Information

Dr. Jens Rafaelsen, Applications Engineer, EDAX

Any EDS spectrum will have two distinct components; the characteristic peaks that originate from transitions between the states of the atoms in the sample and the background (Bremsstrahlung) which comes from continuum radiation emitted from electrons being slowed down as they move through the sample. The figure below shows a carbon coated galena sample (PbS) where the background is below the dark blue line while the characteristic peaks are above.

Some people consider the background an artefact and something to be removed from the spectrum (either through electronics filtering or by subtracting it) but in the TEAM™ software we apply a model based on Kramer’s law that looks as follows:where E is the photon energy, N(E) the number of photons, ε(E) the detector efficiency, A(E) the sample self-absorption, E0 the incident beam energy, and a, b, c are fit parameters¹.

This means that the background is tied to the sample composition and detector characteristic and that you can actually use the background shape and fit/misfit as a troubleshooting tool. Often if you have a bad background, it’s because the sample doesn’t meet the model requirements or the data fed to the model is incorrect. The example below shows the galena spectrum where the model has been fed two different tilt conditions and an overshoot of the background can easily be seen with the incorrect 45 degrees tilt. So, if the background is off in the low energy range, it could be an indication that the surface the spectrum came from was tilted, in which case the quant model will lose accuracy (unless it’s fed the correct tilt value).


This of course means that if your background is off, you can easily spend a long time figuring out what went wrong and why, although it often doesn’t matter too much. To get rid of this complexity we have included a different approach in our APEX™ software that is meant for the entry level user. Instead of doing a full model calculation we apply a Statistics-sensitive Non-linear Iterative Peak-clipping (SNIP) routine². This means that you will always get a good background fit though you lose some of the additional information you get from the Bremsstrahlung model. The images below show part of the difference where the full model includes the steps in the background caused by sample self-absorption while the SNIP filter returns a flat background.

So, which one is better? Well, it depends on where the question is coming from. As a scientist, I would always choose a model where the individual components can be addressed individually and if something looks strange, there will be a physical reason for it. But I also understand that a lot of people are not interested in the details and “just want something that works”. Both the Bremsstrahlung model and the SNIP filter will produce good results as shown in the table below that compares the quantification numbers from the galena sample.

While there’s a slight difference between the two models, the variation is well within what is expected based on statistics and especially considering that the sample is a bit oxidized (as can be seen from the oxygen peak in the spectrum). But the complexity of the SNIP background is significantly reduced relative to the full model and there’s no user input, making it the better choice for the novice analyst of infrequent user.

¹ F. Eggert, Microchim Acta 155, 129–136 (2006), DOI 10.1007/s00604-006-0530-0
² C.G. RYAN et al, Nuclear Instruments and Methods in Physics Research 934 (1988) 396-402

Thoughts from a Summer Intern

Kylie Simpson, Summer Intern 2017, EDAX

This summer at EDAX, I have had the opportunity not only to build upon the skills that I acquired here last summer and throughout my academic year, but also to acquire new skills enabling me to better understand energy dispersive spectroscopy (EDS), materials science, and applied physics. Having access to state-of-the-art microscopes, detectors, and literature has certainly played a large role in my take-away from this summer, but the most valuable aspect of my time at EDAX is the expertise of those around me. Working with the applications team provided me with the opportunity to work alongside the different groups, including the engineering, sales and marketing, and technical support groups, as well as with customers via demos, training courses, and webinars. Not to mention the plethora of knowledge within the applications team itself. The willingness of other EDAX employees not only to help me, but also to explain and teach me how to solve the problems I encountered was extremely helpful.

The major projects I worked on this summer were compiling a user manual for the EDAX APEX™ software, collecting data for a steel library, and tuning a PID system for the thermoelectric cooler used in EDAX detectors. Creating a user manual for APEX™ enabled me to fully understand the software and describe it in a clear and useful way for our customers. I used LaTeX™ software to compile the manual, which exposed me to a very powerful typesetting tool while optimizing the layout and accessibility of the manual. Because I was not involved in the design of APEX™, I was able to write the user manual from the perspective of a new user. As a student and a newer user of EDAX software, I have recognized how useful APEX™ is for beginners and hope that the user manual will help to complement its value.

Figure 1: The EDAX APEX™ User Manual.

The steel library project that I worked on was very interesting because I compiled data that will simplify and aid customers working with steel samples. I collected spectra for nearly 100 steel standards and compared the quant results to the known values to confirm the accuracy of the data. This data will soon be available for purchase by customers who would like to compare the spectra from unknown samples to those of known standards using the spectrum match feature.

Figure 2: Me using one of our scopes to collect data.

Additionally, I was able to work with the engineering team to tune a PID system for the thermoelectric cooler inside all EDAX detectors. The module of each detector must reach a set point temperature in a set period of time and remain stable. By making small changes to the parameters and determining their impact, I ran tests over several weeks to optimize the cooling of the detector. These parameters will be used in future development of EDAX detectors, enabling them to work even more accurately.

Figure 3: The PID system I worked with and me.

Overall, my experience at EDAX has been very positive, providing me with the skills and knowledge to succeed and excel in both academics and my career.